Syntax: HPMIXED Procedure

The following statements are available in PROC HPMIXED:

PROC HPMIXED <options> ;
BY variables ;
CLASS variables ;
EFFECT name = effect-type ( variables </ options> ) ;
ID variables ;
MODEL dependent = <fixed-effects> </ options> ;
RANDOM random-effects </ options> ;
REPEATED repeated-effect </ options> ;
PARMS <(value-list) ...> </ options> ;
TEST fixed-effects </ options> ;
CONTRAST ’label’ contrast-specification <, contrast-specification> <, ...> </ options> ;
ESTIMATE ’label’ contrast-specification <(divisor=n)>
<, ’label’ contrast-specification <(divisor=n)>> <, ...> </options> ;
LSMEANS fixed-effects </ options> ;
NLOPTIONS <options> ;
OUTPUT <OUT=SAS-data-set>
<keyword<(keyword-options)><=name>> </ options> ;
WEIGHT variable ;

Items within angle brackets ( < > ) are optional. The CONTRAST, ESTIMATE, LSMEANS, RANDOM, and TEST statements can appear multiple times; all other statements can appear only once.

The PROC HPMIXED and MODEL statements are required, and the MODEL statement must appear after the CLASS statement if these statements are included. The BY, CLASS, MODEL, ID, OUTPUT, TEST, RANDOM, REPEATED and WEIGHT statements are described in full after the PROC HPMIXED statement in alphabetical order. The EFFECT, is shared with many other procedures. Summary descriptions of functionality and syntax for this statement is also given after the PROC HPMIXED statement in alphabetical order, but you can find full documentation on it in Chapter 19, Shared Concepts and Topics.

Table 45.1 summarizes the basic functions and important options of each PROC HPMIXED statement.

Table 45.1 Summary of PROC HPMIXED Statements



Important Options


Invokes the procedure

DATA= specifies input data set, METHOD= specifies estimation method


Performs multiple PROC HPMIXED analyses in one invocation



Declares qualitative variables that create indicator variables in design matrices



Lists additional variables to be included in predicted values tables



Specifies dependent variable and fixed effects, setting up

S requests solution for fixed-effects parameters, DDFM= specifies denominator degrees of freedom method


Specifies random effects, setting up and

SUBJECT= creates block-diagonality, TYPE= specifies covariance structure, S requests solution for random-effects parameters


Sets up

SUBJECT= creates block-diagonality, TYPE= specifies covariance structure, R= displays estimated blocks of , GROUP= enables between-subject heterogeneity


Specifies a grid of initial values for the covariance parameters

HOLD= and NOITER hold the covariance parameters or their ratios constant, PARMSDATA= reads the initial values from a SAS data set


Constructs custom hypothesis tests

E displays the matrix coefficients


Constructs custom scalar estimates

CL produces confidence limits


Computes least squares means for classification fixed effects

DIFF computes differences of the least squares means, CL produces confidence limits, SLICE= tests simple effects


Specifies a variable by which to weight